"digitalization in oil & gas at an inflection point" by JE ADVISORS, LLC. presented at the 2018 Global SCM Energy Leaders Conference

1. Digitalization in O&G at
an inflection point
May 2018
Joseph Elkhoury

2. content
• what is Digitalization?
• digitalization in O&G
• examples
2

3. what is Digitalization?
3
- Knowledge
- Competence
- Emotions
- Actions
- Objects
Digitalization*:
using Technology to convert
actions and objects into
intangible digital elements
and
creating automated workflows
and cognitive Processes to build
new eco-systems
Processes
Technology
* Simplified and adapted from multiple Digitalization guides
Technology created
ways to re-shape the
material world:
• Internet
• Social Media
• Sharing economy
• Instrumentation
• Data & Cloud
• Automation
Immaterial world
Material world

4. mindsets continue to change
4Sources: Global center for digital transformation 2017
when do you expect the Digitalization
Disruption to occur?
15%
48%
37%
49%
33%
18%
2015 2017
Already occurring Within three years More than three years
how significant will the impact
from this Disruption be?
23% 48% 26%
20% 45% 31%
No Impact Minor Moderate Major Transformative
2015
2017
More than 75%

5. Cloud
$400B
Data
Science
$25B
Big Data
$200B
Sources: numbers rounded from Gartner, Allied Market Research, IDC and others…
market estimates
5
IOT
$1.5T

6. Digitalization in O&G
6

7. what are the barriers for O&G?
7Sources: DNV GL O&G survey
Regulatory obstacles
Previous Digital failures
Access to company data
Risk averse culture
Reliability of the data
Unproven technology
Cybersecurity concerns
Bureaucratic obstacles
Legacy ERP systems
Lack of required skills
Senior Mgmt unaware
Old-fashioned culture
Lack of proper funding

8. the new reality in O&G
Sources: Market Insights, IDC and various others… 8
Main trends impacting the O&G industry:
• Lower commodity price environment
• Abundant U.S. unconventional resources
• More regulations for safety & compliance
• Everyone focused on lowering lifting costs
• Talent & Innovation driving differentiation
Digitalization will enable the O&G industry to reduce
operational risk & increase productivity.
Integration requirements, cyber-security threats and
automation will drive these investments.
1.4B$
2016 2017 2018 2019 2020 2021
Professional Cloud Integration
US O&G Market projections
Limited in-house resources
Inferior on-premise hosting
Inadequate full-data accessibility

9. so why now?
9
a Mobile-device-enabled
Workforce offers plenty
potential to optimize
performance and costs
Instrumentation became
cheaper, is growing and
generating large pools of
under-utilized data
Cloud computing is very
accessible, cost-effective,
AI-enabled and adoption
is growing significantly

10. leaders can cut through the noise
10
recommended steps to Digitalization:
• give Operations a bigger strategic role
• focus on few Trends that are dangerous to ignore
• set ambitious Goals to deliver value
• invest in new skills and build Competence
• predict Customer needs and business models
Sources: modified from Bain and Company
73 %
how executives expect
Digitalization to impact their
Supply Chains
increase speed
and
responsiveness
reduce
overall
costs
Improve ability
to
innovate
65 %
62 %

11. an O&G Digitalization stack example
11
Describe Diagnose Predict Prescribe
AI ProcessesApplicationsPlatformsEdge DevicesInstrumentation
Connectivity
Sensors
M2M
GIS
Drones
Wearables
AR/VR
tools
Robots
3D print
Cognitive
Platforms
PaaS
FOG
Computing
Economics
Assets
Wells
Production
Workforce
Factory
Cyber
Security
Automate
d Processes
Predictive
Analytics
Machine
Learning
Digital
Twins

12. Examples
12

13. U.S. E&P company
13
Descriptive & Diagnostic Analytics
Data At rest and in-stream
• Time-series data storage and retrieval
• Real-time analytics
• Exception-based notifications
• Archives for historical analysis and discovery
$500 Cost of Individual Sensors
$30,000,000 Capital Investment
Benefits
• Reduced asset downtime
• Optimized Production levels
E&P company
21,000 Sensors on injector Wells
10 Total activities monitored
(Extraction rates, Temperature,
Well pressure etc…)
90 times a Day per activity
~18,900,000 daily readings
Source: from a Blue Hill Research paper
1% improvement in production is 3 year payback
5% improvement is less than 1 year payback

14. Multi-national oil & gas company
14
Diagnostic & Predictive Analytics
Data At rest and in-stream
• Used RPA (Robotics Process Automation)
• Automated many manual processes
• Automations tested in various use cases
Benefits
• Manual efforts reduced by 65-80%
• Transactions processed 4X faster
• Cycle time reduced to < 5 minutes
• Pilot saved 1,700 man hours per year
oil & gas company
Initial project:
10 weeks for Proof of concept
2 main RTP (Requisition to Purchase)
workflows automated
analytics and artificial intelligence
initiatives improved overall data
quality by > 95%
Source: from a Deloitte paper
Initial investment payback period less than 12 months

15. trucking fleet
100,000 Sensors on truck fleet
Primary Activities Monitored (Engine
diagnostic codes,
Function of mechanical parts)
10,000 per Truck per Day
~1,000,000 daily readings
Trucking company in O&G
15
Predictive & Prescriptive Analytics
Data At rest and in-stream
• Real-time analytics on streaming data
• Predictive analysis to alert to potential failures
• Integrate with operations to strategically route trucks
Expected Life of Sensors
Life of Truck
Benefits
• Improvements in manufacturing trucks
• Reduced truck repair and maintenance
• Sell Service subscription as new revenue
Source: from a Blue Hill Research paper